What we do
LockedIn Labs brings senior forward-deployed engineers into the work. We connect AI consulting and implementation with cloud, infrastructure, systems, security and recovery engineering, building capabilities your team can run.
How an operating problem becomes a production capability
Name the workflow, system boundary and intended outcome.
Compare behavior against the agreed acceptance criteria.
The client reviews the evidence and holds the production decision.
Enterprise AI and IT engineering
Each engagement starts with an operating problem. We scope the team, system boundary and evidence around the outcome, then stay connected to the engineering that makes it possible. Scope, acceptance criteria and operating ownership are agreed for each engagement.
AI-native transformation
Connect the executive mandate to the workflows, architecture and investment decisions that will deliver it. We work with leadership and operating teams to turn priorities into a governed sequence of production work.
Explore transformationAI and product engineering
Build the product and the systems around it: agent workflows, context, interfaces, evaluation and operations. The same team resolves the architecture, writes the software and carries the work through acceptance.
Explore product engineeringCompliance engineering
Translate operating obligations into implemented controls and traceable evidence. We connect the control design to source systems, remediate the environment and prepare the technical work for assessment.
Explore compliance engineeringCloud and infrastructure engineering
Assess and engineer the cloud and on-premises compute, storage and network foundations your applications depend on. We connect workload requirements to architecture, infrastructure as code, migration sequencing and operational ownership.
Discuss cloud and infrastructureSystems engineering and integration
Connect applications, data and operational systems through interfaces your team can maintain. We resolve dependencies, engineer the integration and test how the connected workflow behaves when a component fails or changes.
Discuss systems engineeringCybersecurity engineering
Assess security architecture and implement technical controls across identities, networks, workloads and software delivery. We turn findings into prioritized remediation and validation evidence that the operating team can inspect.
Discuss cybersecurity engineeringDisaster recovery and business continuity
Map critical operations and their system dependencies, agree recovery priorities with operating owners, and engineer backup, restoration and continuity procedures for the defined scope. Exercise the plan in approved scenarios and record results, gaps and remediation.
Discuss recovery and continuity
Research connected to delivery
Model choices, context design and integration behavior deserve more than a quick demo. Our lab brings those questions into focused experiments, tools and engineering guidance that can inform the next build.
Agent Console, MOEModels, AI SDLC and Context Harness make parts of that work available for others to inspect and use.
Explore the labPublic work
These resources expose specific parts of our engineering practice. They give a technical team something concrete to review before a conversation begins.
A published guide to the AI software development lifecycle, with engineering decisions and evidence carried through delivery.
Local visibility into agent usage, tokens and cost, with MIT-licensed tooling.
A browser-local workbench for designing context, tool boundaries, evaluation and handoff.
Usage and cost records measure activity and spend. Productivity and quality conclusions require outcome measures and a defined comparison.
Bring the operating problem, the systems it touches and the outcome you need. We will help define the engineering path.
